Description Usage Arguments Details Value Author(s) References See Also Examples
Random generation and density function for a finite mixture of Gamma distribution.
1 2 3 |
n |
number of observations. |
x |
vector of quantiles. |
weight |
vector of probability weights, with length equal to number of components (k). This is assumed to sum to 1; if not, it is normalized. |
alpha |
vector of non-negative parameters of the Gamma distribution. |
beta |
vector of non-negative parameters of the Gamma distribution. |
Sampling from finite mixture of Gamma distribution, with density:
Pr(x|\underline{w}, \underline{α}, \underline{β}) = ∑_{i=1}^{k} w_{i} Gamma(x|α_{i}, β_{i}),
where
Gamma(x|α_{i}, β_{i})=\frac{(β_{i})^{α_{i}}}{Γ(α_{i})} x^{α_{i}-1} e^{-β_{i}x}.
Generated data as an vector with size n.
Reza Mohammadi a.mohammadi@uva.nl
Mohammadi, A., Salehi-Rad, M. R., and Wit, E. C. (2013) Using mixture of Gamma distributions for Bayesian analysis in an M/G/1 queue with optional second service. Computational Statistics, 28(2):683-700, doi: 10.1007/s00180-012-0323-3
Mohammadi, A., and Salehi-Rad, M. R. (2012) Bayesian inference and prediction in an M/G/1 with optional second service. Communications in Statistics-Simulation and Computation, 41(3):419-435, doi: 10.1080/03610918.2011.588358
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ## Not run:
n = 10000
weight = c( 0.6 , 0.3 , 0.1 )
alpha = c( 100 , 200 , 300 )
beta = c( 100/3, 200/4, 300/5 )
data = rmixgamma( n = n, weight = weight, alpha = alpha, beta = beta )
hist( data, prob = TRUE, nclass = 30, col = "gray" )
x = seq( -20, 20, 0.05 )
densmixgamma = dmixnorm( x, weight, alpha, beta )
lines( x, densmixgamma, lwd = 2 )
## End(Not run)
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Loading required package: BDgraph
Loading required package: Matrix
Loading required package: igraph
Attaching package: 'igraph'
The following objects are masked from 'package:stats':
decompose, spectrum
The following object is masked from 'package:base':
union
Attaching package: 'BDgraph'
The following object is masked from 'package:igraph':
compare
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